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公开(公告)号:US20220039055A1
公开(公告)日:2022-02-03
申请号:US16944723
申请日:2020-07-31
Applicant: ZEBRA TECHNOLOGIES CORPORATION
Inventor: Douglas C. Bowman , Richard Lawerance Woodburn , Edward W. Geiger , Yu Wan , Janakiraman Gopalan , Thomas E. Warner , Eric T. Tokubo , Carl S. Mower
Abstract: A method in a computing device includes: via a short-range interface of the computing device, detecting a plurality of beacons emitted by another computing device, each beacon containing an identifier of the other computing device; obtaining respective proximity indicators corresponding to the beacons; generating a first set of aggregated attributes from the proximity indicators; storing the first set of aggregated attributes in association with the identifier of the other computing device; and transmitting the first set of aggregated attributes to a server configured to detect physical proximity between the computing device and the other computing device based on the first set of aggregated attributes.
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公开(公告)号:US11562268B2
公开(公告)日:2023-01-24
申请号:US16899355
申请日:2020-06-11
Applicant: ZEBRA TECHNOLOGIES CORPORATION
Inventor: Thomas Dorris , Carl S. Mower
Abstract: Methods and devices for determining a load vector on an object are disclosed herein. An example method includes collecting location observations related to the object. The example method further includes filtering the location observations to determine an estimated model path. The example method further includes outputting a set of data from the estimated model path, wherein the set of data includes a model location, a model velocity, a model acceleration, and a model jerk. The example method further includes calculating a load vector from the set of data, scaling the load vector via a scaling index, and transmitting the scaled load vector to a remote device.
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公开(公告)号:US20210390425A1
公开(公告)日:2021-12-16
申请号:US16899355
申请日:2020-06-11
Applicant: ZEBRA TECHNOLOGIES CORPORATION
Inventor: Thomas Dorris , Carl S. Mower
Abstract: Methods and devices for determining a load vector on an object are disclosed herein. An example method includes collecting location observations related to the object. The example method further includes filtering the location observations to determine an estimated model path. The example method further includes outputting a set of data from the estimated model path, wherein the set of data includes a model location, a model velocity, a model acceleration, and a model jerk. The example method further includes calculating a load vector from the set of data, scaling the load vector via a scaling index, and transmitting the scaled load vector to a remote device.
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